Ching-Hsien Ko

OF Ontario Tower Buzzers

Age 20 L/R 6'3" / 215 lbs A HR +8%BB -8% Svc 0.0 · Ctrl thru 2035

Overview

APROSPECTMiLBFA 2036

OGV OFP35OGV rank#523ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	17	ROKDSL LAD Bauti…	40	.241/.450/.448	1	1	65	—	.121/.275/.182
2025	18	A/ROK2 orgs	364	.310/.439/.439	4	6	87	—	.235/.334/.321
2026	19	ALAD	531	.260/.395/.470	21	1	90	—	.210/.314/.370
2027PROJMLE	20	MLBLAD	614	.213/.312/.346	15	6	88	0.1
2028PROJ34% MLB	21	MLBLAD	174	.216/.315/.361	5	2	95	0.1
2029PROJ48% MLB	22	MLBLAD	263	.221/.319/.374	8	4	99	0.4

Next 3 projected WAR 0.6Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2035Service0.0First FA2036

2027MiLB2028MiLB2029MiLB2030Pre-Arb$0.8M2031Pre-Arb$0.9M2032Pre-Arb$0.9M2033Arb-1$3M2034Arb-2$5M+1

Skills · percentileMiLB Statcast 2026 A

ISO84

BB%84

wOBA76

wRC+73

Chase%72

K%49

Career WAR0.2 WAR median (P10 -0.2 / P90 26, comp-based) · star 15% · didn't stick 59%

CompsCarter Jensen (age 20) · Ryan McMahon (age 20) · Moisés Ballesteros (age 19)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 210 proj PA

wRC+†88

AVG/OBP/SLG.211 / .309 / .343

PA210

HR5

K%29

BB%11

ISO133

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$19M ctrl surplus

Contract

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status MiLB

MLB Debut 2030

Service 0 yrs (est)

Team Control Through 2035

First FA Year 2036

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2030
2028	MiLB	still in minors · estimated debut 2030
2029	MiLB	still in minors · estimated debut 2030
2030	Pre-Arb	$0.8M	+0.6	$2M	+$1M
2031	Pre-Arb	$0.9M	+0.7	$2M	+$1M
2032	Pre-Arb	$0.9M	+0.8	$2M	+$2M
2033	Arb-1	$3M	+0.8	$2M	+$0.2M
2034	Arb-2	$5M	+0.7	$2M	+$0.0M (cut)
2035	Arb-3	$7M	+0.6	$1M	+$0.0M (cut)
Totals		$6M		$11M	+$5M

Career Stats + Projections

Real MLB stats plus park-adjusted projections — this season (so far / rest / full), then future seasons and career totals.

show model inputsbasis chips: RAW = as recorded · CTX = with park/league context · A+C = actual + context combined · MLE = level/park-neutral

Methodology▸ how these numbers are built

All seasons translated to park-neutral MLB-equivalent (MLE) and combined per year. 2027 = full-season projection (no games played yet). 2028+ via Advanced Marcel + aging curve.

Year	Age	Lvl	Team	MLB%	PA	AB	H	2B	3B	HR	BB	SO	HBP	SB	CS	AVG	OBP	SLG	OPS	ISO	BABIP	K%	BB%	wOBA	wRC+	BAT	RUN	FLD	POS	REP	WAR
▸ Career — actual stats, one row per stint (as recorded, no adjustments)
2024	17	ROK	DSL LAD Bautista	—	40	29	7	3	0	1	11	7	0	1	1	241	450	448	898	207	286	18	28	408	65	—	—	—	—	—	—
2025	18	A	Rancho Cucamonga Quakes	—	138	114	25	3	2	0	23	32	1	1	0	219	355	281	636	61	305	23	17	304	47	—	—	—	—	—	—
2025	18	ROK	ACL Dodgers	—	226	180	66	15	2	4	39	40	5	5	3	367	491	539	1.030	172	449	18	17	453	111	—	—	—	—	—	—
2026	19	A	Ontario Tower Buzzers	—	531	430	112	17	5	21	89	128	7	1	1	260	395	470	865	209	318	24	17	383	90	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2024	17	ROK MLE	DSL LAD Bautista	—	40	33	4	2	0	0	7	9	0	1	1	121	275	182	457	61	183	22	18	265	65	—	—	—	—	—	—
2025	18	A MLE	Rancho Cucamonga Quakes	—	138	120	21	2	2	0	17	44	1	1	0	175	283	225	508	50	278	32	12	238	47	—	—	—	—	—	—
2025	18	ROK MLE	ACL Dodgers	—	226	195	53	10	1	3	24	58	5	5	3	272	366	379	746	108	366	26	11	332	111	—	—	—	—	—	—
2026	19	A MLE	Ontario Tower Buzzers	—	531	457	96	14	4	17	62	174	7	1	1	210	314	370	683	160	286	33	12	301	90	—	—	—	—	—	—
2024	17	ROK MLE	DSL LAD Bautista	—	40	33	4	2	0	0	7	9	0	1	1	121	275	182	457	61	167	22	18	265	65	—	—	—	—	—	—
2024	17	ROK RAW	DSL LAD Bautista	—	40	29	7	3	0	1	11	7	0	1	1	241	450	448	898	207	286	18	28	408	65	—	—	—	—	—	—
2025	18	ROK MLE	2 teams	—	364	315	76	13	3	3	41	102	6	6	3	241	340	330	670	89	344	28	11	296	87	—	—	—	—	—	—
2025	18	ROK RAW	2 teams	—	364	294	91	18	4	4	62	72	6	6	3	310	439	439	878	129	395	20	17	397	87	—	—	—	—	—	—
2026	19	A MLE	Ontario Tower Buzzers	—	531	457	96	14	4	17	62	174	7	1	1	210	314	370	683	160	292	33	12	301	90	—	—	—	—	—	—
2026	19	A RAW	Ontario Tower Buzzers	—	531	430	112	17	5	21	89	128	7	1	1	260	395	470	865	209	318	24	17	383	90	—	—	—	—	—	—
2024	17	ROK MLE	DSL LAD Bautista	—	40	33	4	2	0	0	7	9	0	1	1	121	275	182	457	61	183	22	18	265	65	—	—	—	—	—	—
2025	18	ROK MLE	2 teams	—	364	314	76	13	3	3	41	102	6	6	3	242	340	331	671	89	333	28	11	296	87	—	—	—	—	—	—
2026	19	A MLE	Ontario Tower Buzzers	—	531	457	96	14	4	17	62	174	7	1	1	210	314	370	683	160	286	33	12	301	90	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	17	ROK MLE	DSL LAD Bautista	—	40	33	4	2	0	0	7	9	0	1	1	121	275	182	457	61	183	22	18	265	65	—	—	—	—	—	—
2025	18	ROK MLE	2 teams	—	364	314	76	13	3	3	41	102	6	6	3	242	340	331	671	89	333	28	11	296	87	—	—	—	—	—	—
2026	19	A MLE	Ontario Tower Buzzers	—	531	457	96	14	4	17	62	174	7	1	1	210	314	370	683	160	286	33	12	301	90	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	20	MLB MLE	LAD	0%	614	533	113	18	4	15	69	181	7	6	2	213	312	346	658	133	289	29	11	299	88	-8	+0	-2	-4	+13	0.1
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	21	MLB MLE	LAD	34%	507	438	97	16	4	14	58	144	6	7	3	219	318	365	683	146	290	28	11	309	95	-3	+0	-1	-3	+11	0.4
2029	22	MLB MLE	LAD	48%	543	470	106	17	4	16	62	150	6	9	3	224	322	378	700	154	290	28	11	315	99	-0	+1	-1	-3	+12	0.8
2030	23	MLB MLE	LAD	54%	560	485	111	18	4	17	63	152	7	10	3	228	325	386	711	158	291	27	11	319	102	+1	+1	-0	-3	+12	1.1
2031	24	MLB MLE	LAD	55%	578	501	116	19	4	18	65	154	7	10	3	230	326	391	718	161	292	27	11	322	104	+3	+1	-0	-3	+13	1.3
2032	25	MLB MLE	LAD	56%	590	512	119	20	4	19	66	156	7	10	4	231	327	394	721	163	292	26	11	323	105	+3	+0	-0	-4	+13	1.3
2033	26	MLB MLE	LAD	56%	599	520	121	20	4	19	67	158	7	11	4	231	327	394	720	162	292	26	11	323	104	+3	+1	-0	-4	+13	1.3
2034	27	MLB MLE	LAD	55%	596	517	120	20	4	19	67	158	7	10	4	230	326	391	717	161	291	27	11	321	103	+2	+0	-0	-4	+13	1.2
2035	28	MLB MLE	LAD	55%	585	509	116	19	4	18	65	157	6	9	4	228	324	386	710	158	290	27	11	318	102	+1	+0	-1	-4	+13	1.0
2036	29	MLB MLE	LAD	53%	568	494	111	18	3	17	63	154	6	8	4	226	321	379	700	154	288	27	11	315	99	-1	+0	-1	-3	+12	0.7
2037	30	MLB MLE	LAD	53%	552	480	106	17	3	16	61	151	6	7	4	222	317	371	688	149	286	27	11	310	96	-3	-0	-2	-3	+12	0.4
2038	31	MLB MLE	LAD	52%	534	466	101	16	3	15	58	148	5	5	5	218	312	361	673	143	283	28	11	304	92	-5	-1	-3	-3	+12	-0.1
2028	21	MLB CTX	LAD	34%	174	150	33	5	1	5	20	50	2	2	1	216	315	361	676	145	283	29	11	306	95	-1	+0	-0	-1	+4	0.1
2029	22	MLB CTX	LAD	48%	263	228	51	8	2	8	30	73	3	4	1	221	319	374	694	154	284	28	11	312	99	-0	+0	-0	-2	+6	0.4
2030	23	MLB CTX	LAD	54%	304	263	59	9	2	10	34	82	4	5	2	224	322	383	704	158	284	27	11	316	102	+1	+0	-0	-2	+7	0.6
2031	24	MLB CTX	LAD	55%	320	277	63	10	2	10	36	85	4	6	2	227	323	388	711	161	285	27	11	319	104	+1	+0	-0	-2	+7	0.7
2032	25	MLB CTX	LAD	56%	330	286	65	10	2	11	37	87	4	6	2	228	324	391	715	163	285	26	11	320	105	+2	+0	-0	-2	+7	0.8
2033	26	MLB CTX	LAD	56%	337	292	67	11	2	11	38	89	4	6	2	228	324	390	714	162	285	26	11	320	104	+2	+0	-0	-2	+7	0.8
2034	27	MLB CTX	LAD	55%	330	286	65	10	2	11	37	88	4	6	2	227	323	388	710	161	284	27	11	319	103	+1	+0	-0	-2	+7	0.7
2035	28	MLB CTX	LAD	55%	321	278	63	10	2	10	36	86	4	5	2	225	321	383	703	158	283	27	11	316	102	+1	+0	-0	-2	+7	0.6
2036	29	MLB CTX	LAD	53%	303	263	58	9	2	9	34	82	3	4	2	222	318	376	694	154	282	27	11	312	99	-0	+0	-1	-2	+7	0.4
2037	30	MLB CTX	LAD	53%	290	253	56	9	1	9	32	79	3	4	2	219	314	368	682	149	280	27	11	308	96	-1	+0	-1	-2	+6	0.2
2038	31	MLB CTX	LAD	52%	278	243	52	8	1	8	30	77	3	2	3	215	309	358	667	143	277	28	11	302	92	-3	-1	-1	-2	+6	-0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	3250	2819	632	99	19	102	364	878	38	50	21	224	321	381	702	157	285	27	11	314	98	+2	+2	-5	-20	+70	5.1
/ 162G	—	A+C		—	650	564	126	20	4	20	73	176	8	10	4	223	321	379	701	156	285	27	11	314	98	+0	+0	-1	-4	+14	1.0
Career	—	MLE		—	7357	6379	1438	235	49	213	829	2029	85	106	47	225	323	378	700	152	293	28	11	314	98	-1	+3	-10	-39	+139	9.4
/ 162G	—	MLE		—	650	564	127	21	4	19	73	179	8	9	4	225	323	378	701	152	292	28	11	314	98	-0	+0	-1	-4	+14	1.0

How the minor-league lines were translated

One row per minor-league stint. Open a row to see each step: the raw rate, the park adjustment, the league/level factor, the age adjustment (hitters) and the resulting MLE rate. Factors are the same ones listed on the MLE Factors page.

2026 AOntario Tower Buzzers · 531 PAwOBA .376 → .301 (−74)K% 24.1% → 32.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.11%	÷1.000	×1.360	—	—	32.78%
BB% (unintentional) /PA	16.38%	÷1.000	×0.690	—	×1.030	11.64%
HBP% /PA	1.32%	—	×0.780	—	×1.030	1.06%
Singles /BIP	22.85%	÷1.000	×0.920	×0.980	×1.030	21.22%
Doubles /BIP	5.63%	÷1.000	×0.830	×0.980	×1.030	4.72%
Triples /BIP	1.66%	÷1.000	×0.910	×0.980	×1.030	1.52%
Home runs /BIP	6.95%	÷1.000	×0.800	—	×1.030	5.73%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 20 vs a level average of 22.0 → +3.0% on BB/HBP/hit rates (2.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.980.

Result: wOBA .376 → .301; ISO .209 → .168; BABIP .318 → .286. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2025 ROKACL Dodgers · 226 PAwOBA .446 → .332 (−114)K% 17.7% → 25.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.70%	÷0.993	×1.440	—	—	25.67%
BB% (unintentional) /PA	17.26%	÷0.997	×0.620	—	×1.008	10.81%
HBP% /PA	2.21%	—	×0.720	—	×1.008	1.60%
Singles /BIP	32.14%	÷0.996	×0.820	×1.050	×1.008	28.00%
Doubles /BIP	10.71%	÷1.102	×0.720	×1.050	×1.008	7.41%
Triples /BIP	1.43%	÷1.060	×0.720	×1.050	×1.008	1.03%
Home runs /BIP	2.86%	÷1.187	×0.780	—	×1.008	1.89%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 137, 1B 99, 2B 120, 3B 112, K 99, BB 99 — applied at half strength. Age: age 19 vs a level average of 19.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .446 → .332; ISO .172 → .118; BABIP .449 → .366. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2025 ARancho Cucamonga Quakes · 138 PAwOBA .298 → .238 (−60)K% 23.2% → 31.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.19%	÷0.987	×1.360	—	—	31.95%
BB% (unintentional) /PA	16.67%	÷0.981	×0.690	—	×1.045	12.25%
HBP% /PA	0.72%	—	×0.780	—	×1.045	0.59%
Singles /BIP	24.39%	÷1.004	×0.920	×0.981	×1.045	22.90%
Doubles /BIP	3.66%	÷1.054	×0.830	×0.981	×1.045	2.95%
Triples /BIP	2.44%	÷1.150	×0.910	×0.981	×1.045	1.98%
Home runs /BIP	0.00%	÷1.055	×0.800	—	×1.045	0.00%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 111, 1B 101, 2B 111, 3B 130, K 97, BB 96 — applied at half strength. Age: age 19 vs a level average of 22.0 → +4.5% on BB/HBP/hit rates (3.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.981.

Result: wOBA .298 → .238; ISO .061 → .046; BABIP .305 → .278. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2024 DSLDSL LAD Bautista · 40 PAwOBA .399 → .265 (−134)K% 17.5% → 21.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.50%	÷0.994	×1.220	—	—	21.49%
BB% (unintentional) /PA	27.50%	÷1.051	×0.700	—	×1.008	18.46%
HBP% /PA	0.00%	—	×0.700	—	×1.008	0.00%
Singles /BIP	13.64%	÷0.998	×0.680	—	×1.008	9.36%
Doubles /BIP	13.64%	÷0.963	×0.600	—	×1.008	8.56%
Triples /BIP	0.00%	÷1.150	×0.600	—	×1.008	0.00%
Home runs /BIP	4.55%	÷1.059	×0.470	—	×1.008	2.03%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 112, 1B 100, 2B 92, 3B 130, K 99, BB 110 — applied at half strength. Age: age 18 vs a level average of 18.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average).

Result: wOBA .399 → .265; ISO .207 → .121; BABIP .286 → .183. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Kole Calhounlast yr '23 career totals — 11 seasons, 4,963 PA	7.5	4,963	179	33	242	316	418	-54	-33	8.3	9.6
/162	664	24	4	-7.3	-4.4	1.1	pk7: 11
#2Will Venablelast yr '15 career totals — 8 seasons, 3,127 PA	4.7	3,127	81	135	251	317	406	-20	-4	8.9	8.7
/162	664	17	29	-4.2	-0.8	1.9	pk7: 9
#3Leroy Stanton'70-'78 * career totals — 7 seasons, 2,883 PA	4.3	2,883	77	36	245*	314*	430*	-33	-1	6.5	7.8
/162	664	18	8	-7.7	-0.2	1.5	pk7: 9
#4Scott Spiezio'96-'07 * career totals — 11 seasons, 4,412 PA	6.6	4,412	119	33	245*	318*	406*	-34	-15	7.5	7.8
/162	664	18	5	-5.2	-2.3	1.1	pk7: 8
#5Ron Swoboda'65-'73 * career totals — 8 seasons, 2,924 PA	4.4	2,924	73	20	243*	329*	417*	-30	-1	6.8	7.3
/162	664	17	5	-6.7	-0.3	1.5	pk7: 8
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 7 projected seasons	5.2	3,461	103	52	227	319	382	-21	+0	7.8	6.9
/162	664	20	10	-4.0	+0.0	1.5	pk7: 6
#6Michael Saunderslast yr '17 career totals — 8 seasons, 2,711 PA	4.1	2,711	81	55	233	305	399	-12	-13	4.1	4.5
/162	664	20	13	-2.9	-3.2	1.0	pk7: 5

Career Path Comps

What happened to players with a similar stat profile at this age · Y-axis: wRC+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

		Scouting				At Match Age									Next 3 Yrs									Peak 3 Yrs
Comp	Age	HIT	PWR	SPD	EYE	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR
Ching-Hsien Ko (OGILVIE)	20	—	—	—	—	211/309/343	132	289	5	2	29%	11%	88	+0.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
●Carter Jensen 2023 · A	20	38→48	42→55	45→50	49	189/279/298	109	272	9	7	32%	11%	66	-1.1	205/296/340	135	284	14	9	30%	11%	82	-0.0	233/312/421	188	299	22	7	28%	10%	105	+1.6
●Ryan McMahon 2015 · A	20	43→53	46→55	43→45	39	211/269/348	136	312	12	6	35%	7%	73	-0.6	240/294/393	153	349	15	7	33%	6%	93	+0.8	232/313/397	165	299	19	6	28%	10%	103	+1.6
●Moisés Ballesteros 2023 · A	19	41→51	46→50	45→40	50	210/283/334	125	261	14	5	25%	9%	76	-0.4	248/309/379	131	301	14	4	21%	8%	95	+0.9	266/327/397	130	316	14	3	20%	8%	104	+1.4
✕Nick Weglarz 2008 · A	20	44→48	50	44→45	46	222/301/378	155	310	19	3	33%	9%	93	+0.8	231/317/384	153	294	16	5	25%	10%	99	+1.3	231/323/389	157	284	16	5	23%	10%	101	+1.0
✕Nomar Mazara 2015 · AA	20	43→53	46→55	43→40	43	214/278/347	133	297	14	3	32%	8%	76	-0.4	247/306/386	139	303	16	2	23%	7%	95	+1.0	249/308/420	171	291	21	3	22%	7%	102	+1.4
✕Canaan Smith-Njigba 2019 · A	20	46→51	41→45	46→55	51	218/304/317	98	298	9	7	28%	10%	79	-0.2	237/308/353	116	333	10	11	29%	9%	88	+0.5	242/319/359	118	343	9	15	29%	10%	91	+0.4
✕Bo Naylor 2021 · A	21	41→46	44→55	51→50	42	206/261/333	127	283	11	7	30%	7%	66	-1.1	204/287/354	150	283	17	13	32%	10%	82	-0.0	218/311/396	178	274	21	12	27%	11%	100	+1.0
✕Nicky Delmonico 2013 · A	21	42→48	48→55	50→45	47	216/285/353	137	265	16	8	25%	8%	80	-0.1	211/277/350	139	287	14	7	30%	8%	77	-0.3	237/306/397	160	290	18	4	24%	8%	96	+0.8
✕Tirso Ornelas 2019 · A	19	44→54	41→50	50→45	45	214/282/314	100	297	8	5	30%	8%	70	-0.9	195/261/274	79	285	5	5	31%	8%	53	-2.1	262/321/391	130	320	13	7	22%	7%	99	+1.1
✕Rio Ruiz 2014 · A	20	45→54	44→50	50→40	45	221/278/350	129	289	10	8	27%	7%	76	-0.4	241/308/352	111	311	9	4	23%	9%	88	+0.4	246/316/351	105	316	8	2	23%	9%	88	+0.4
●Dylan Carlson 2019 · A	20	44→53	44→55	45→50	46	213/286/329	116	288	11	6	28%	8%	76	-0.4	237/305/399	162	302	17	10	26%	8%	98	+1.2	246/317/424	178	308	20	8	26%	8%	109	+1.4
✕Abimelec Ortiz 2022 · A	20	36→42	47→60	50→40	54	185/296/323	138	225	14	8	24%	11%	80	-0.2	204/271/370	166	279	22	5	34%	7%	80	-0.2	215/282/406	191	269	25	2	30%	7%	90	+0.5
✕Xavier Isaac 2024 · A	20	45→44	51→55	55→50	48	228/303/392	164	299	18	9	29%	9%	96	+1.0	216/302/390	174	327	21	12	37%	10%	96	+1.0	205/305/390	184	309	24	14	38%	12%	94	+0.6
✕Akil Baddoo 2019 · A	20	43→53	43→50	56→55	47	207/283/329	122	293	8	13	30%	9%	74	-0.6	215/284/346	131	317	11	16	33%	9%	78	-0.3	238/319/386	148	309	15	24	26%	11%	100	+0.9
✕Max Clark 2024 · A	19	44→53	42→45	51→55	48	207/292/314	106	308	9	11	33%	10%	74	-0.5	238/314/357	119	306	11	17	24%	9%	92	+0.7	245/323/369	124	304	11	19	22%	10%	96	+0.9
✕Yanquiel Fernández 2023 · A	20	46→48	49→55	50→30	41	234/281/390	156	301	16	4	28%	6%	87	+0.4	231/271/379	148	297	18	2	28%	5%	81	-0.1	227/268/370	143	283	18	1	26%	5%	76	-0.3
●Chris Parmelee 2009 · A	21	39→49	49→55	47→45	43	196/274/346	150	297	17	5	38%	9%	75	-0.5	231/300/364	133	301	14	3	26%	9%	88	+0.5	259/324/406	147	305	15	1	19%	8%	107	+1.8
✕Isan Díaz 2016 · A	20	44→43	47→55	48→45	41	216/276/358	142	306	13	9	32%	7%	78	-0.3	206/276/342	136	304	13	8	34%	8%	74	-0.5	212/290/379	167	275	21	5	30%	9%	86	+0.2
●Heriberto Hernández 2021 · A	21	45→48	49→60	46→50	47	220/300/377	156	305	15	6	31%	9%	92	+0.7	206/285/353	147	323	17	6	38%	9%	81	-0.1	222/305/421	199	281	26	11	30%	10%	104	+1.3
✕Billy McKinney 2015 · A	20	47→57	43→60	49→45	46	227/295/339	113	298	10	6	26%	8%	81	-0.1	242/302/360	118	307	9	4	23%	7%	88	+0.4	222/283/407	185	267	20	2	25%	7%	91	+0.5

Ching-Hsien Ko

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps